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Linking Household Survey and Administrative Record Data: What Should the Matching Variables Be?

Author

Listed:
  • Stephen P. Jenkins
  • Peter Lynn
  • Annette Jäckle
  • Emanuela Sala
Abstract
Linkages of household survey responses with administrative data may be based on unique individual identifiers or on survey respondent characteristics. The benefits gained from using unique identifiers need to be assessed in the light of potential problems such as non-response and measurement error. We report on a study that linked survey responses to UK government agency records on benefits and tax credits in five different ways. One matched on a respondent-supplied National Insurance Number and the other four used different combinations of sex, name, address, and date of birth. As many linkages were made using matches on sex, date of birth, and post-code, or on sex, date of birth, first name and family name, as were made using matches on self-reported National Insurance Number, and the former were also relatively accurate when assessed in terms of false positive and false negative rates. The five independent matching exercises also shed light on the potential returns from hierarchical and pooled matching.

Suggested Citation

  • Stephen P. Jenkins & Peter Lynn & Annette Jäckle & Emanuela Sala, 2005. "Linking Household Survey and Administrative Record Data: What Should the Matching Variables Be?," Discussion Papers of DIW Berlin 489, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp489
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    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.43285.de/dp489.pdf
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    References listed on IDEAS

    as
    1. P. Taylor, Mark & Böheim, René, 2000. "From the dark end of the street to the bright side of the road? investigating the returns to residential mobility in Britain," ISER Working Paper Series 2000-38, Institute for Social and Economic Research.
    2. Stephen P. Jenkins & Lorenzo Cappellari & Peter Lynn & Annette Jäckle & Emanuela Sala, 2006. "Patterns of consent: evidence from a general household survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 701-722, October.
    3. Simon Burgess & Deborah Wilson, 2003. "Ethnic Segregation in England's Schools," The Centre for Market and Public Organisation 03/086, The Centre for Market and Public Organisation, University of Bristol, UK.
    4. Lynn, Peter & Jäckle, Annette & Sala, Emanuela & P. Jenkins, Stephen, 2004. "Validation of survey data on income and employment: the ISMIE experience," ISER Working Paper Series 2004-14, Institute for Social and Economic Research.
    5. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," Stata Journal, StataCorp LP, vol. 3(3), pages 278-294, September.
    6. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Lynn, Peter & Sala, Emanuela, 2004. "The contact and response process in business surveys: lessons from a multimode survey of employers in the UK," ISER Working Paper Series 2004-12, Institute for Social and Economic Research.
    2. Stephen P. Jenkins & Lorenzo Cappellari & Peter Lynn & Annette Jäckle & Emanuela Sala, 2006. "Patterns of consent: evidence from a general household survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 701-722, October.
    3. Lynn, Peter & Jäckle, Annette & Sala, Emanuela & P. Jenkins, Stephen, 2004. "Validation of survey data on income and employment: the ISMIE experience," ISER Working Paper Series 2004-14, Institute for Social and Economic Research.
    4. Lynn, Peter & Sala, Emanuela, 2005. "The impact of a mixed-mode data collection design on non response bias on a business survey," ISER Working Paper Series 2005-16, Institute for Social and Economic Research.
    5. Tom W. Smith & Jibum Kim, 2013. "An Assessment of the Multi-level Integrated Database Approach," The ANNALS of the American Academy of Political and Social Science, , vol. 645(1), pages 185-221, January.
    6. Hartmann, Josef & Krug, Gerhard, 2007. "Verknüpfung von Befragungs- und Prozessdaten : Selektivität durch fehlende Zustimmung der Befragten?," IAB-Discussion Paper 200713, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. Lynn, Peter & Jäckle, Annette & Sala, Emanuela & P. Jenkins, Stephen, 2004. "The impact of interviewing method on measurement error in panel survey measures of benefit receipt: evidence from a validation study," ISER Working Paper Series 2004-28, Institute for Social and Economic Research.

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